The mobile application model has significantly changed consumption of content managed on the Internet. For example, joining social media and instant messaging applications, increasingly popular mobile gaming applications such as Angry Birds, are some of the latest types of applications to send mobile signaling and data consumption skyrocketing. Angry Birds is just one example of the many available applications that constantly signal the mobile network for updates at hundreds and even thousands of times per hour. As such, traditional practices of providing all-you-can-eat data plans have become a thing of the past. The data tsunami is affecting the mobile ecosystem as a whole, and end-users are feeling the brunt of the wrath as operators scramble to find the best solution.
The applications that contribute to mobile data consumption can further include, for example, push email, instant messaging, visual voicemail, voice and video telephony, and others which may require an always-on of frequent IP connections and frequent transmit of small bits of data. Further, these applications poll their host servers with varying polling characteristics, due to the nature of the application, user activity, and/or nature of data being exchanged. For example, one category of polling can be represented by a persistent IP connection, such as one established by long polling or COMET style push, which is a web application model where long-held request (e.g., long-held HTTP requests) allows server to push data to the client when this data becomes available.
The persistent connection allows emulation of content push from server to client (e.g., mobile client). Specifically, when a response is not available when the request is sent, the server holds the request until information becomes available to be sent to the client. In general, the client immediately re-issues a request to the server, which the server then responds to or holds until a response is available. This behavior of long polls or other types of persistent connections is different from other types of polling. Due to the different caching requirements of different types of polling, different classes of polling patterns, such as long poll patterns and characteristics need to be detected for effective caching and assessment of cacheability.